Skeleton-based Approaches based on Machine Vision: A Survey
This survey provides a structured overview of skeleton-based approaches for researchers and practitioners working on various machine vision tasks, helping them understand current applications and address specific issues.
This paper surveys skeleton-based approaches in machine vision, categorizing them by application fields and tasks. It aims to provide a comprehensive overview of how these methods are applied to solve specific problems.
Recently, skeleton-based approaches have achieved rapid progress on the basis of great success in skeleton representation. Plenty of researches focus on solving specific problems according to skeleton features. Some skeleton-based approaches have been mentioned in several overviews on object detection as a non-essential part. Nevertheless, there has not been any thorough analysis of skeleton-based approaches attentively. Instead of describing these techniques in terms of theoretical constructs, we devote to summarizing skeleton-based approaches with regard to application fields and given tasks as comprehensively as possible. This paper is conducive to further understanding of skeleton-based application and dealing with particular issues.